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Abstract

In this paper, a multi-dimensional equilibrium allocation model of water resources was developed based on the groundwater multiple loop iteration technique. The proposed model is an integrated framework of three modules respectively corresponding to the input layer, operation layer, and feedback layer in the allocation process. Firstly, a prediction model integrating the genetic algorithm-back propagation (GA-BP) model, the general regression neural network (GRNN) model, and the support vector machine (SVM) model was built to predict the future reservoir runoff, and the results were entered into the database of an optimal allocation model. Furthermore, taking exploitable groundwater as the feedback factor, the water resource optimal allocation model was continuously optimized. Also, the groundwater multiple loop iteration technique was applied to the feedback process. The proposed model was successfully applied to a typical region in Jinan, Eastern China. The uncertainties of future reservoir runoff and exploitable groundwater were taken into account. The results revealed that groundwater represented 36.6% of water supply in the base year, indicating that it is the main water source in Jinan. However, the amount of groundwater mining was decreased after considering the exploitable groundwater. The developed framework provides a comprehensive approach towards optimal future allocation of water resources, especially for the regions with overexploited groundwater.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).